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---
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune
This model is a fine-tuned version of [UBC-NLP/MARBERTv2](https://huggingface.co/UBC-NLP/MARBERTv2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1711
- Precision: 0.7538
- Recall: 0.7902
- F1: 0.7716
- Accuracy: 0.9536
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 25
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1914 | 1.0 | 121 | 0.1169 | 0.7655 | 0.7369 | 0.7510 | 0.9536 |
| 0.0946 | 2.0 | 242 | 0.1192 | 0.7952 | 0.7334 | 0.7631 | 0.9558 |
| 0.0643 | 3.0 | 363 | 0.1336 | 0.7471 | 0.7932 | 0.7695 | 0.9537 |
| 0.0428 | 4.0 | 484 | 0.1585 | 0.7312 | 0.7957 | 0.7621 | 0.9517 |
| 0.0286 | 5.0 | 605 | 0.1711 | 0.7538 | 0.7902 | 0.7716 | 0.9536 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
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